How to remove variable in R?

A comprehensive guide on how to remove variable in R.

In programming, variables play a crucial role in storing and managing data. They serve as memory spaces where you can stash information for later use. In the R programming language, variables are no exception, and knowing how to manipulate them is essential.

This guide focuses on a specific aspect of variable handling: how to remove all variables in R from your current session. Whether you're cleaning up your workspace or starting fresh, this knowledge can come in handy.

Explore Identifying Product Bundles from Sales Data Using R Language 

How to remove a variable in R?

Let's dive into the step-by-step process of how to clear all variables in an R session.

Step 1: Assigning Three Variables

Before we can remove variables, we first need to create them. Let's assign values to three different variables, each with a different data type:

a = 'hello'

b = 3.5

c = as.integer(8.9)

To verify that the assignment was successful, we can use the cat() function to print the variables:

cat(a, b, c)

You should see the output displaying the values of these variables.

Step 2: Removing Variables

Now, it's time to remove the variables. We use the rm() function for this purpose. By providing the argument list = ls(), we ensure that all variables are removed from the list of objects in the current session. Keep in mind that this will also remove any functions you may have assigned in the session.

rm(list = ls())

To confirm that the variables have been removed, try to print one of them, such as a, using the cat() function:

cat(a)

You'll likely receive an error message indicating that the object 'a' was not found, confirming that the variables have been successfully removed from your R session.

Explore Exciting R projects with ProjectPro!

Mastering the art of variable manipulation, including removal, is a key skill in R programming and data analysis. We recommend you delve deeper into the world of R programming by working on a few projects in data science as it will enhance your knowledge and capabilities. And if you are interested in a one stop solution that will let you learn about using R programming for data analysis and machine learning applications, look no further than ProjectPro. ProjectPro offers a variety of projects in data science and big data that you must work on if you are looking forward to building a career in these fields in the most efficient way.

So, why wait? Elevate your skills with ProjectPro and embark on a rewarding career in the realm of data analysis and interpretation.

What Users are saying..

profile image

Ray han

Tech Leader | Stanford / Yale University
linkedin profile url

I think that they are fantastic. I attended Yale and Stanford and have worked at Honeywell,Oracle, and Arthur Andersen(Accenture) in the US. I have taken Big Data and Hadoop,NoSQL, Spark, Hadoop... Read More

Relevant Projects

Insurance Pricing Forecast Using XGBoost Regressor
In this project, we are going to talk about insurance forecast by using linear and xgboost regression techniques.

Detectron2 Object Detection and Segmentation Example Python
Object Detection using Detectron2 - Build a Dectectron2 model to detect the zones and inhibitions in antibiogram images.

MLOps Project on GCP using Kubeflow for Model Deployment
MLOps using Kubeflow on GCP - Build and deploy a deep learning model on Google Cloud Platform using Kubeflow pipelines in Python

Azure Text Analytics for Medical Search Engine Deployment
Microsoft Azure Project - Use Azure text analytics cognitive service to deploy a machine learning model into Azure Databricks

Build a Graph Based Recommendation System in Python -Part 1
Python Recommender Systems Project - Learn to build a graph based recommendation system in eCommerce to recommend products.

Recommender System Machine Learning Project for Beginners-4
Collaborative Filtering Recommender System Project - Comparison of different model based and memory based methods to build recommendation system using collaborative filtering.

AWS MLOps Project for Gaussian Process Time Series Modeling
MLOps Project to Build and Deploy a Gaussian Process Time Series Model in Python on AWS

Time Series Analysis with Facebook Prophet Python and Cesium
Time Series Analysis Project - Use the Facebook Prophet and Cesium Open Source Library for Time Series Forecasting in Python

AWS MLOps Project to Deploy Multiple Linear Regression Model
Build and Deploy a Multiple Linear Regression Model in Python on AWS

Personalized Medicine: Redefining Cancer Treatment
In this Personalized Medicine Machine Learning Project you will learn to classify genetic mutations on the basis of medical literature into 9 classes.